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library(plotly)##
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## layout
goals <- read.csv("data/TransposedGoals.csv")ggplot(data = goals, aes(x = Avg_DisLikelihood, y = Avg_HonLikelihood))+
geom_point()+
theme_bw()+
labs(title = "Scatterplot of Goal Expectancies",
x = "Likelihood that dishonesty would achieve goal",
y = "Likelihood that honesty would achieve goal")ggsave("goals_scatter.png", plot = last_plot(), device = "png")## Saving 4 x 4 in image
goals %>%
summarize(r = cor(Avg_DisLikelihood, Avg_HonLikelihood))## r
## 1 -0.8360762
ggplot(goals, aes(x = Diff_Likelihood))+
geom_histogram(fill = "grey", color = "black")+
theme_bw()## `stat_bin()` using `bins = 30`. Pick better value with `binwidth`.
goals %>%
summary## CASE_LBL R1_Hon R2_Hon R3_Hon
## Length:155 Min. :1.000 Min. :1.000 Min. :1.000
## Class :character 1st Qu.:2.000 1st Qu.:2.000 1st Qu.:3.000
## Mode :character Median :3.000 Median :3.000 Median :4.000
## Mean :2.948 Mean :3.065 Mean :3.523
## 3rd Qu.:4.000 3rd Qu.:4.000 3rd Qu.:4.000
## Max. :5.000 Max. :5.000 Max. :5.000
##
## R4_Hon R5_Hon R6_Hon R7_Hon Goal
## Min. :1.000 Min. :1.000 Min. :1.000 Min. :1.00 Min. : 1.0
## 1st Qu.:2.000 1st Qu.:3.000 1st Qu.:2.000 1st Qu.:2.00 1st Qu.: 39.5
## Median :2.000 Median :4.000 Median :3.000 Median :3.00 Median : 78.0
## Mean :2.755 Mean :3.574 Mean :3.271 Mean :3.09 Mean : 78.0
## 3rd Qu.:4.000 3rd Qu.:5.000 3rd Qu.:5.000 3rd Qu.:4.00 3rd Qu.:116.5
## Max. :5.000 Max. :5.000 Max. :5.000 Max. :5.00 Max. :155.0
##
## R1_Dis R2_Dis R3_Dis R4_Dis
## Min. :1.000 Min. :1.000 Min. :1.000 Min. :1.000
## 1st Qu.:3.000 1st Qu.:2.000 1st Qu.:2.000 1st Qu.:2.000
## Median :3.000 Median :3.000 Median :3.000 Median :4.000
## Mean :3.084 Mean :2.619 Mean :3.135 Mean :3.226
## 3rd Qu.:4.000 3rd Qu.:3.000 3rd Qu.:4.000 3rd Qu.:5.000
## Max. :5.000 Max. :5.000 Max. :5.000 Max. :5.000
##
## R5_Dis R6_Dis R7_Dis Avg_HonLikelihood
## Min. :1.000 Min. :1.000 Min. :1 Min. :1.000
## 1st Qu.:2.000 1st Qu.:1.000 1st Qu.:2 1st Qu.:2.429
## Median :4.000 Median :3.000 Median :3 Median :3.000
## Mean :3.497 Mean :2.604 Mean :3 Mean :3.175
## 3rd Qu.:5.000 3rd Qu.:4.000 3rd Qu.:4 3rd Qu.:4.143
## Max. :5.000 Max. :5.000 Max. :5 Max. :5.000
## NA's :1
## Avg_DisLikelihood Diff_Likelihood
## Min. :1.000 Min. :-4.0000
## 1st Qu.:2.000 1st Qu.:-1.4286
## Median :3.286 Median :-0.2857
## Mean :3.023 Mean : 0.1524
## 3rd Qu.:3.857 3rd Qu.: 2.1429
## Max. :5.000 Max. : 4.0000
##
polar_goals <- goals %>%
filter(Diff_Likelihood >= 2.1 | Diff_Likelihood <= -1.4,
Avg_HonLikelihood >= 3.0 | Avg_HonLikelihood <= 2.4,
Avg_DisLikelihood >= 3.2 | Avg_DisLikelihood <= 2.00)
ggplot(data = polar_goals, aes(x = Avg_DisLikelihood, y = Avg_HonLikelihood))+
geom_point(position = "jitter")+
theme_bw()polar_goals <- polar_goals %>%
mutate(likelihood = if_else(Avg_HonLikelihood > 3.99, "Honesty", "Dishonesty"))polar_goals %>%
group_by(likelihood) %>%
count()## # A tibble: 2 × 2
## # Groups: likelihood [2]
## likelihood n
## <chr> <int>
## 1 Dishonesty 28
## 2 Honesty 36
polar_goals %>%
filter(likelihood == "Honesty") %>%
arrange(desc(Diff_Likelihood)) %>%
arrange(desc(Avg_HonLikelihood))## CASE_LBL R1_Hon R2_Hon R3_Hon R4_Hon R5_Hon R6_Hon R7_Hon Goal
## 1 Hon_CorrectInaccurate 5 5 5 5 5 5 5 57
## 2 Hon_AvoidLiar 5 5 5 5 5 5 5 24
## 3 Hon_NeedToKnow 4 5 5 5 5 5 5 12
## 4 Hon_ExpFeelings 4 5 5 5 5 5 5 8
## 5 Hon_ImpInfo 4 5 5 5 5 5 5 27
## 6 Hon_BeYourself 5 5 5 5 5 5 4 70
## 7 Hon_ExpressHowFeel 4 5 5 5 5 5 5 74
## 8 Hon_Self_Image 4 4 5 5 5 5 5 48
## 9 Hon_AvoidViolat 4 4 5 5 5 5 5 37
## 10 Hon_ShareMyself 5 4 5 5 5 5 4 49
## 11 Hon_BeAuth 4 4 5 5 5 5 4 73
## 12 Hon_ShowHonesty 4 4 5 4 5 5 5 9
## 13 Hon_Chest 3 5 5 5 5 4 5 28
## 14 Hon_AvoidFake 4 4 5 4 5 5 5 61
## 15 Hon_RightThing 4 4 5 4 5 5 5 2
## 16 Hon_AvoidConf 4 4 5 4 5 5 5 43
## 17 Hon_FosterUnd 4 4 4 5 5 5 5 104
## 18 Hon_CommClear 4 5 4 4 5 5 5 66
## 19 Hon_AvoidGross 5 1 5 5 5 5 5 33
## 20 Hon_AcknFault 4 4 5 4 4 5 5 1
## 21 Hon_BeBestSelf 4 3 5 4 5 5 5 23
## 22 Hon_GainTrust 3 4 4 5 5 5 5 22
## 23 Hon_AvoidPollut 5 3 5 4 5 5 4 34
## 24 Hon_TreatResp 5 3 4 5 5 5 4 69
## 25 Hon_AvoidMis 4 4 4 5 5 4 4 17
## 26 Hon_ReduUncertainty 4 4 4 3 5 5 5 41
## 27 Hon_ConveyInfo 3 3 5 4 5 5 5 46
## 28 Hon_GoodEx 4 3 4 4 5 5 5 16
## 29 Hon_BeUnd 3 3 4 5 5 5 5 65
## 30 Hon_EffecCoord 2 4 4 4 5 5 5 45
## 31 Hon_HelpDoBett 4 4 4 4 3 5 5 51
## 32 Hon_HelpProduc 3 4 5 3 5 5 4 71
## 33 Hon_VoidCov 4 1 4 5 5 5 5 6
## 34 Hon_FacilWork 3 4 4 4 5 5 4 39
## 35 Hon_HelpImprov 4 3 4 4 5 5 4 40
## 36 Hon_FacilPlan 3 3 4 4 5 5 4 21
## R1_Dis R2_Dis R3_Dis R4_Dis R5_Dis R6_Dis R7_Dis Avg_HonLikelihood
## 1 1 1 1 1 1 1 1 5.000000
## 2 1 1 1 2 1 1 1 5.000000
## 3 2 1 1 1 1 1 1 4.857143
## 4 3 1 1 1 1 1 1 4.857143
## 5 2 1 2 1 1 1 1 4.857143
## 6 2 1 1 1 1 1 2 4.857143
## 7 2 1 2 1 1 1 1 4.857143
## 8 2 2 1 2 1 1 1 4.714286
## 9 2 2 2 1 1 2 3 4.714286
## 10 3 2 1 5 1 1 1 4.714286
## 11 1 1 1 1 1 1 1 4.571429
## 12 3 2 1 1 1 1 1 4.571429
## 13 4 1 2 1 1 1 1 4.571429
## 14 2 2 2 1 2 1 1 4.571429
## 15 2 2 2 1 2 2 1 4.571429
## 16 2 2 1 2 2 2 1 4.571429
## 17 4 2 2 1 1 1 1 4.571429
## 18 3 2 2 2 2 1 1 4.571429
## 19 1 1 1 1 1 1 1 4.428571
## 20 4 2 1 1 1 1 1 4.428571
## 21 3 2 1 1 1 2 1 4.428571
## 22 3 2 2 2 2 2 1 4.428571
## 23 2 3 2 2 1 2 2 4.428571
## 24 2 3 2 1 2 2 2 4.428571
## 25 2 2 2 2 1 1 1 4.285714
## 26 2 2 2 2 1 1 1 4.285714
## 27 3 3 1 1 1 1 1 4.285714
## 28 2 2 2 2 2 1 1 4.285714
## 29 3 3 2 1 2 1 1 4.285714
## 30 3 2 2 1 1 1 1 4.142857
## 31 2 2 1 2 1 2 2 4.142857
## 32 3 2 2 1 1 2 2 4.142857
## 33 3 1 2 2 2 3 1 4.142857
## 34 3 2 2 1 1 2 3 4.142857
## 35 2 2 2 2 2 2 2 4.142857
## 36 3 2 2 1 1 1 2 4.000000
## Avg_DisLikelihood Diff_Likelihood likelihood
## 1 1.000000 4.000000 Honesty
## 2 1.142857 3.857143 Honesty
## 3 1.142857 3.714286 Honesty
## 4 1.285714 3.571429 Honesty
## 5 1.285714 3.571429 Honesty
## 6 1.285714 3.571429 Honesty
## 7 1.285714 3.571429 Honesty
## 8 1.428571 3.285714 Honesty
## 9 1.857143 2.857143 Honesty
## 10 2.000000 2.714286 Honesty
## 11 1.000000 3.571429 Honesty
## 12 1.428571 3.142857 Honesty
## 13 1.571429 3.000000 Honesty
## 14 1.571429 3.000000 Honesty
## 15 1.714286 2.857143 Honesty
## 16 1.714286 2.857143 Honesty
## 17 1.714286 2.857143 Honesty
## 18 1.857143 2.714286 Honesty
## 19 1.000000 3.428571 Honesty
## 20 1.571429 2.857143 Honesty
## 21 1.571429 2.857143 Honesty
## 22 2.000000 2.428571 Honesty
## 23 2.000000 2.428571 Honesty
## 24 2.000000 2.428571 Honesty
## 25 1.571429 2.714286 Honesty
## 26 1.571429 2.714286 Honesty
## 27 1.571429 2.714286 Honesty
## 28 1.714286 2.571429 Honesty
## 29 1.857143 2.428571 Honesty
## 30 1.571429 2.571429 Honesty
## 31 1.714286 2.428571 Honesty
## 32 1.857143 2.285714 Honesty
## 33 2.000000 2.142857 Honesty
## 34 2.000000 2.142857 Honesty
## 35 2.000000 2.142857 Honesty
## 36 1.714286 2.285714 Honesty
polar_goals %>%
filter(likelihood == "Dishonesty") %>%
arrange(Diff_Likelihood) %>%
arrange(desc(Avg_DisLikelihood))## CASE_LBL R1_Hon R2_Hon R3_Hon R4_Hon R5_Hon R6_Hon R7_Hon Goal
## 1 Hon_GetSometh 1 1 1 1 1 1 1 98
## 2 Hon_BeSeeBett 2 1 1 1 1 1 1 142
## 3 Hon_KeepLieGo 1 1 1 1 1 1 1 130
## 4 Hon_HidePers 1 2 1 1 1 1 1 75
## 5 Hon_CoverUp 3 1 2 1 1 1 1 117
## 6 Hon_AvoidArgu 2 2 2 1 2 2 2 108
## 7 Hon_AvoidVuln 2 2 1 1 1 3 2 121
## 8 Hon_AvoidBad 2 2 2 2 1 2 3 136
## 9 Hon_ProtFeelings 2 3 2 1 3 2 2 13
## 10 Hon_TrickSomeone 2 1 1 1 1 1 1 122
## 11 Hon_AvoidOverre 2 3 2 1 2 1 2 93
## 12 Hon_Secret 5 1 2 1 2 2 1 76
## 13 Hon_AvoidUncomf 2 2 3 1 3 2 1 91
## 14 Hon_AvoidAwk 2 3 2 1 2 2 3 83
## 15 Hon_AvoidReje 2 2 2 1 3 2 2 140
## 16 Hon_LookBetter 2 3 3 2 2 1 2 31
## 17 Hon_DecMyself 1 1 1 1 1 1 1 105
## 18 Hon_ProtPriv 1 2 3 1 3 2 2 101
## 19 Hon_AvoidCorrec 2 1 2 1 3 4 2 103
## 20 Hon_AvoidWaves 2 2 4 3 2 2 1 55
## 21 Hon_AvoidOther 2 3 3 2 1 1 1 147
## 22 Hon_StopConv 2 2 3 2 2 2 1 109
## 23 Hon_PresrvEng 2 3 2 1 2 1 3 115
## 24 Hon_KeepBrief 2 3 3 1 2 2 1 151
## 25 Hon_ConfToRole 2 2 2 1 3 3 2 155
## 26 Hon_Surprise 3 3 3 1 1 1 1 77
## 27 Hon_ConfuseOthers 2 1 2 1 2 1 1 99
## 28 Hon_ConvMyse 2 2 1 1 3 1 2 106
## R1_Dis R2_Dis R3_Dis R4_Dis R5_Dis R6_Dis R7_Dis Avg_HonLikelihood
## 1 5 5 5 5 5 5 5 1.000000
## 2 5 5 5 4 5 5 4 1.142857
## 3 5 4 4 4 5 5 5 1.000000
## 4 4 3 5 5 5 5 5 1.142857
## 5 4 4 5 4 5 5 5 1.428571
## 6 4 4 5 5 5 5 4 1.857143
## 7 4 4 5 5 5 3 5 1.714286
## 8 4 4 5 4 5 5 4 2.000000
## 9 4 4 4 5 5 5 4 2.142857
## 10 4 4 5 3 5 5 4 1.142857
## 11 4 4 5 4 5 4 3 1.857143
## 12 2 5 5 5 5 2 5 2.000000
## 13 3 3 5 5 5 4 4 2.000000
## 14 4 3 5 5 5 3 4 2.142857
## 15 4 2 5 5 4 4 4 2.000000
## 16 3 3 5 5 5 3 4 2.142857
## 17 5 5 3 4 3 3 4 1.000000
## 18 3 4 4 5 5 2 4 2.000000
## 19 4 2 4 5 5 3 4 2.142857
## 20 4 3 4 4 5 3 4 2.285714
## 21 4 2 4 4 5 3 4 1.857143
## 22 3 3 4 4 5 3 4 2.000000
## 23 3 3 4 4 5 3 4 2.000000
## 24 3 2 4 4 5 4 4 2.000000
## 25 4 3 4 5 4 2 4 2.142857
## 26 3 3 4 4 5 2 4 1.857143
## 27 3 3 4 1 4 4 5 1.428571
## 28 3 3 5 4 3 1 4 1.714286
## Avg_DisLikelihood Diff_Likelihood likelihood
## 1 5.000000 -4.000000 Dishonesty
## 2 4.714286 -3.571429 Dishonesty
## 3 4.571429 -3.571429 Dishonesty
## 4 4.571429 -3.428571 Dishonesty
## 5 4.571429 -3.142857 Dishonesty
## 6 4.571429 -2.714286 Dishonesty
## 7 4.428571 -2.714286 Dishonesty
## 8 4.428571 -2.428571 Dishonesty
## 9 4.428571 -2.285714 Dishonesty
## 10 4.285714 -3.142857 Dishonesty
## 11 4.142857 -2.285714 Dishonesty
## 12 4.142857 -2.142857 Dishonesty
## 13 4.142857 -2.142857 Dishonesty
## 14 4.142857 -2.000000 Dishonesty
## 15 4.000000 -2.000000 Dishonesty
## 16 4.000000 -1.857143 Dishonesty
## 17 3.857143 -2.857143 Dishonesty
## 18 3.857143 -1.857143 Dishonesty
## 19 3.857143 -1.714286 Dishonesty
## 20 3.857143 -1.571429 Dishonesty
## 21 3.714286 -1.857143 Dishonesty
## 22 3.714286 -1.714286 Dishonesty
## 23 3.714286 -1.714286 Dishonesty
## 24 3.714286 -1.714286 Dishonesty
## 25 3.714286 -1.571429 Dishonesty
## 26 3.571429 -1.714286 Dishonesty
## 27 3.428571 -2.000000 Dishonesty
## 28 3.285714 -1.571429 Dishonesty
So, first my goal is the make an interactive version of our scatterplot from earlier, that tells you the name of each goal when you hover over it. I also want to use color to more clearly emphasize the size of the difference between honesty and dishonesty scores for each goal.
#absolute value differences
goals <- goals %>%
mutate(abs_diff = abs(Diff_Likelihood))
goals_interactive <- goals %>%
ggplot(aes(x = Avg_DisLikelihood, y = Avg_HonLikelihood, label = CASE_LBL))+
geom_point(aes(color = abs_diff), position = "jitter")+
theme_bw()
ggplotly(tooltip = c("label"))[Should we make the goals have full names? Is that too much trouble?]
What I would like to do now is select a few exemplar goals, which seem to (a) tap into most of the important themes/contents of goals and (b) represent a goals from the range of honesty vs. dishonesty
goals %>%
arrange(Diff_Likelihood)## CASE_LBL R1_Hon R2_Hon R3_Hon R4_Hon R5_Hon R6_Hon R7_Hon Goal
## 1 Hon_GetSometh 1 1 1 1 1 1 1 98
## 2 Hon_KeepLieGo 1 1 1 1 1 1 1 130
## 3 Hon_BeSeeBett 2 1 1 1 1 1 1 142
## 4 Hon_HidePers 1 2 1 1 1 1 1 75
## 5 Hon_CoverUp 3 1 2 1 1 1 1 117
## 6 Hon_TrickSomeone 2 1 1 1 1 1 1 122
## 7 Hon_DecMyself 1 1 1 1 1 1 1 105
## 8 Hon_AvoidArgu 2 2 2 1 2 2 2 108
## 9 Hon_AvoidVuln 2 2 1 1 1 3 2 121
## 10 Hon_AvoidBad 2 2 2 2 1 2 3 136
## 11 Hon_ProtFeelings 2 3 2 1 3 2 2 13
## 12 Hon_AvoidOverre 2 3 2 1 2 1 2 93
## 13 Hon_Secret 5 1 2 1 2 2 1 76
## 14 Hon_AvoidUncomf 2 2 3 1 3 2 1 91
## 15 Hon_AvoidJudg 2 2 2 2 3 3 3 80
## 16 Hon_AvoidAwk 2 3 2 1 2 2 3 83
## 17 Hon_AvoidDoing 3 4 3 1 2 3 2 95
## 18 Hon_ConfuseOthers 2 1 2 1 2 1 1 99
## 19 Hon_AvoidPunish 2 4 2 2 3 2 3 118
## 20 Hon_AvoidReje 2 2 2 1 3 2 2 140
## 21 Hon_LookBetter 2 3 3 2 2 1 2 31
## 22 Hon_AvoidAng 2 3 3 4 2 3 2 84
## 23 Hon_AvoidAwkwardness 2 3 3 2 3 2 2 96
## 24 Hon_ProtPriv 1 2 3 1 3 2 2 101
## 25 Hon_AvoidOther 2 3 3 2 1 1 1 147
## 26 Hon_MakeFeelBet 2 3 3 2 3 2 2 148
## 27 Hon_Surprise 3 3 3 1 1 1 1 77
## 28 Hon_AvoidCorrec 2 1 2 1 3 4 2 103
## 29 Hon_StopConv 2 2 3 2 2 2 1 109
## 30 Hon_PresrvEng 2 3 2 1 2 1 3 115
## 31 Hon_AvoidOtherDisap 2 3 3 2 3 4 2 132
## 32 Hon_KeepBrief 2 3 3 1 2 2 1 151
## 33 Hon_AvoidWaves 2 2 4 3 2 2 1 55
## 34 Hon_ConvMyse 2 2 1 1 3 1 2 106
## 35 Hon_AvoidEmb 2 3 3 3 2 2 3 112
## 36 Hon_ConfToRole 2 2 2 1 3 3 2 155
## 37 Hon_EnsurSafe 2 3 3 1 2 3 3 78
## 38 Hon_KeepPeace 2 3 3 3 2 3 2 82
## 39 Hon_BePolite 4 2 3 2 2 2 2 124
## 40 Hon_GentleOther 2 3 3 2 3 2 2 126
## 41 Hon_AvoidStandOut 2 2 4 1 3 1 3 54
## 42 Hon_Story 3 3 3 4 2 2 2 90
## 43 Hon_AvoidSuff 3 2 3 1 4 2 3 102
## 44 Hon_PleaseOther 2 3 3 2 5 3 2 125
## 45 Hon_GetAhead 3 2 3 2 3 2 3 145
## 46 Hon_ProtectWorr 2 3 4 1 3 2 3 149
## 47 Hon_GetWhatIWant 3 4 3 2 3 3 3 81
## 48 Hon_AvoidHassle 2 3 4 1 4 2 3 94
## 49 Hon_ControlOther 3 3 3 2 2 3 2 111
## 50 Hon_Strategy 2 1 2 2 2 1 2 116
## 51 Hon_AvoidLose 3 3 3 2 3 3 3 134
## 52 Hon_AvoidDisap 2 3 4 2 3 5 2 29
## 53 Hon_AvoidDisSomeone 2 3 3 2 2 4 3 89
## 54 Hon_GetAtten 3 4 4 2 3 2 3 97
## 55 Hon_ExplMyself 2 2 2 1 5 1 4 114
## 56 Hon_EntertSelf 3 2 3 1 1 2 2 123
## 57 Hon_HurtReput 3 3 3 3 3 3 3 129
## 58 Hon_SeemSmart 3 3 3 2 4 2 3 131
## 59 Hon_GetAct 2 4 3 2 3 3 2 133
## 60 Hon_HurtOther 2 3 4 3 3 3 3 26
## 61 Hon_FollowScript 4 2 4 1 2 3 2 53
## 62 Hon_ToLookGood 3 3 3 3 4 3 3 110
## 63 Hon_KeepSmooth 3 2 3 2 3 3 2 138
## 64 Hon_MakeLike 3 2 3 3 3 2 2 139
## 65 Hon_SeemFriendly 2 4 3 2 3 2 2 143
## 66 Hon_GetEven 3 3 4 4 2 2 2 153
## 67 Hon_GetWant 2 4 3 2 4 5 3 4
## 68 Hon_ProtEmb 3 2 4 4 3 4 2 11
## 69 Hon_SeemGen 3 3 3 3 3 4 2 144
## 70 Hon_AvoidAccu 1 3 4 5 5 3 2 146
## 71 Hon_SayExpec 3 2 4 2 4 3 2 154
## 72 Hon_DisapParents 2 3 4 2 3 4 4 25
## 73 Hon_BeAttrac 3 3 2 2 4 2 2 32
## 74 Hon_FeelTrue 1 1 3 1 3 3 4 107
## 75 Hon_NotFeelBad 2 3 4 1 5 4 2 79
## 76 Hon_FollowNorms.0 4 4 4 2 4 3 2 86
## 77 Hon_PositvDir 3 3 3 2 3 3 2 120
## 78 Hon_HowToAct 3 3 4 1 4 1 1 135
## 79 Hon_Consequences 2 1 4 2 3 2 3 3
## 80 Hon_BeKind 2 3 3 3 5 4 3 14
## 81 Hon_FollowNorms 3 3 4 2 4 4 2 18
## 82 Hon_HelpGetSom 3 3 5 1 3 3 3 50
## 83 Hon_ProtectRel 3 4 4 3 5 5 1 119
## 84 Hon_GetOtherDo 2 5 4 2 4 5 2 141
## 85 Hon_ChangeBeh 3 4 4 3 3 4 3 85
## 86 Hon_GainConfi 2 4 4 3 4 3 3 100
## 87 Hon_ContinConvo 4 3 3 4 3 2 2 150
## 88 Hon_AvProb 4 4 4 3 4 5 3 5
## 89 Hon_KeepFromEmb 3 2 4 4 3 5 3 15
## 90 Hon_BeHumb 3 3 4 2 3 1 3 59
## 91 Hon_FacilConvo.0 3 3 3 3 4 3 2 87
## 92 Hon_WasteTime 3 3 4 3 5 4 4 92
## 93 Hon_ImprEffic 3 2 3 2 5 4 5 42
## 94 Hon_AvoidSusp 3 3 4 3 5 1 4 44
## 95 Hon_FacilConvo 4 3 3 2 5 3 3 20
## 96 Hon_GetDeserve 4 4 4 2 5 4 3 47
## 97 Honesty_137 2 3 5 3 5 5 3 137
## 98 Hon_ActNat 4 3 4 2 5 4 3 62
## 99 Hon_BeBest 3 2 3 2 5 5 5 88
## 100 Hon_DrawAtten 3 4 4 2 5 2 2 113
## 101 Hon_Autonomy 4 3 4 3 4 2 5 128
## 102 Hon_PutInPlace 4 4 4 4 3 2 4 56
## 103 Hon_BeResp 4 4 4 4 5 4 4 60
## 104 Hon_MakeFair 4 3 4 2 5 4 2 127
## 105 Hon_ShowFairness 3 3 4 4 4 4 3 10
## 106 Hon_AvoidGuilt 2 4 4 4 5 5 4 19
## 107 Hon_GetHonesty 4 4 4 4 4 4 4 38
## 108 Hon_MakeWorth 3 3 4 4 3 4 4 63
## 109 Hon_RecogProb 4 3 5 2 2 1 4 7
## 110 Hon_KeepFirm 3 3 4 3 3 3 5 35
## 111 Hon_SeekHelp 3 4 5 5 4 3 4 58
## 112 Hon_FeelClose 3 3 4 4 4 5 5 152
## 113 Hon_BeAware 4 4 4 1 5 1 5 36
## 114 Hon_MakeMean 3 4 4 4 4 4 4 64
## 115 Hon_VoidCov 4 1 4 5 5 5 5 6
## 116 Hon_AvBreakTrust 4 4 5 5 5 5 2 30
## 117 Hon_FacilWork 3 4 4 4 5 5 4 39
## 118 Hon_HelpImprov 4 3 4 4 5 5 4 40
## 119 Hon_HelpSolveProb 4 4 4 4 5 5 4 52
## 120 Hon_Deepen 3 4 4 5 4 5 5 67
## 121 Hon_LongRun 4 5 4 4 5 5 4 72
## 122 Hon_FacilPlan 3 3 4 4 5 5 4 21
## 123 Hon_AvoidCaught 5 4 4 4 5 5 5 68
## 124 Hon_HelpProduc 3 4 5 3 5 5 4 71
## 125 Hon_GainTrust 3 4 4 5 5 5 5 22
## 126 Hon_AvoidPollut 5 3 5 4 5 5 4 34
## 127 Hon_HelpDoBett 4 4 4 4 3 5 5 51
## 128 Hon_BeUnd 3 3 4 5 5 5 5 65
## 129 Hon_TreatResp 5 3 4 5 5 5 4 69
## 130 Hon_GoodEx 4 3 4 4 5 5 5 16
## 131 Hon_EffecCoord 2 4 4 4 5 5 5 45
## 132 Hon_AvoidMis 4 4 4 5 5 4 4 17
## 133 Hon_ReduUncertainty 4 4 4 3 5 5 5 41
## 134 Hon_ConveyInfo 3 3 5 4 5 5 5 46
## 135 Hon_ShareMyself 5 4 5 5 5 5 4 49
## 136 Hon_CommClear 4 5 4 4 5 5 5 66
## 137 Hon_AcknFault 4 4 5 4 4 5 5 1
## 138 Hon_RightThing 4 4 5 4 5 5 5 2
## 139 Hon_BeBestSelf 4 3 5 4 5 5 5 23
## 140 Hon_AvoidViolat 4 4 5 5 5 5 5 37
## 141 Hon_AvoidConf 4 4 5 4 5 5 5 43
## 142 Hon_FosterUnd 4 4 4 5 5 5 5 104
## 143 Hon_Chest 3 5 5 5 5 4 5 28
## 144 Hon_AvoidFake 4 4 5 4 5 5 5 61
## 145 Hon_ShowHonesty 4 4 5 4 5 5 5 9
## 146 Hon_Self_Image 4 4 5 5 5 5 5 48
## 147 Hon_AvoidGross 5 1 5 5 5 5 5 33
## 148 Hon_ExpFeelings 4 5 5 5 5 5 5 8
## 149 Hon_ImpInfo 4 5 5 5 5 5 5 27
## 150 Hon_BeYourself 5 5 5 5 5 5 4 70
## 151 Hon_BeAuth 4 4 5 5 5 5 4 73
## 152 Hon_ExpressHowFeel 4 5 5 5 5 5 5 74
## 153 Hon_NeedToKnow 4 5 5 5 5 5 5 12
## 154 Hon_AvoidLiar 5 5 5 5 5 5 5 24
## 155 Hon_CorrectInaccurate 5 5 5 5 5 5 5 57
## R1_Dis R2_Dis R3_Dis R4_Dis R5_Dis R6_Dis R7_Dis Avg_HonLikelihood
## 1 5 5 5 5 5 5 5 1.000000
## 2 5 4 4 4 5 5 5 1.000000
## 3 5 5 5 4 5 5 4 1.142857
## 4 4 3 5 5 5 5 5 1.142857
## 5 4 4 5 4 5 5 5 1.428571
## 6 4 4 5 3 5 5 4 1.142857
## 7 5 5 3 4 3 3 4 1.000000
## 8 4 4 5 5 5 5 4 1.857143
## 9 4 4 5 5 5 3 5 1.714286
## 10 4 4 5 4 5 5 4 2.000000
## 11 4 4 4 5 5 5 4 2.142857
## 12 4 4 5 4 5 4 3 1.857143
## 13 2 5 5 5 5 2 5 2.000000
## 14 3 3 5 5 5 4 4 2.000000
## 15 4 4 5 4 5 5 4 2.428571
## 16 4 3 5 5 5 3 4 2.142857
## 17 4 3 5 5 5 5 5 2.571429
## 18 3 3 4 1 4 4 5 1.428571
## 19 4 4 5 5 5 5 4 2.571429
## 20 4 2 5 5 4 4 4 2.000000
## 21 3 3 5 5 5 3 4 2.142857
## 22 4 4 5 5 5 5 4 2.714286
## 23 4 3 4 5 5 5 4 2.428571
## 24 3 4 4 5 5 2 4 2.000000
## 25 4 2 4 4 5 3 4 1.857143
## 26 4 4 4 5 5 4 4 2.428571
## 27 3 3 4 4 5 2 4 1.857143
## 28 4 2 4 5 5 3 4 2.142857
## 29 3 3 4 4 5 3 4 2.000000
## 30 3 3 4 4 5 3 4 2.000000
## 31 4 4 5 5 5 4 4 2.714286
## 32 3 2 4 4 5 4 4 2.000000
## 33 4 3 4 4 5 3 4 2.285714
## 34 3 3 5 4 3 1 4 1.714286
## 35 4 3 5 5 5 3 4 2.571429
## 36 4 3 4 5 4 2 4 2.142857
## 37 4 3 4 5 4 3 4 2.428571
## 38 2 4 5 4 5 4 4 2.571429
## 39 3 4 4 4 5 3 4 2.428571
## 40 3 3 5 4 5 4 3 2.428571
## 41 3 2 4 4 5 4 3 2.285714
## 42 3 3 5 5 3 4 5 2.714286
## 43 3 3 3 5 5 4 4 2.571429
## 44 4 3 4 5 4 4 5 2.857143
## 45 3 2 5 5 5 3 4 2.571429
## 46 3 4 3 4 5 4 4 2.571429
## 47 4 3 4 5 5 4 4 3.000000
## 48 3 3 4 4 5 3 5 2.714286
## 49 4 3 4 3 5 3 4 2.571429
## 50 3 1 3 2 5 2 4 1.714286
## 51 4 3 5 4 5 4 3 2.857143
## 52 4 4 3 4 5 4 4 3.000000
## 53 4 4 3 4 5 4 2 2.714286
## 54 4 3 4 5 5 3 4 3.000000
## 55 2 3 5 4 5 3 2 2.428571
## 56 3 1 4 4 3 2 4 2.000000
## 57 3 3 4 3 5 5 5 3.000000
## 58 3 3 5 5 5 2 4 2.857143
## 59 4 3 4 3 5 3 4 2.714286
## 60 3 3 4 4 5 4 4 3.000000
## 61 3 2 2 5 5 3 4 2.571429
## 62 3 3 4 5 5 3 5 3.142857
## 63 4 2 4 3 5 2 4 2.571429
## 64 3 3 3 4 5 4 2 2.571429
## 65 4 2 3 5 5 2 3 2.571429
## 66 4 3 4 3 4 3 5 2.857143
## 67 4 3 4 5 5 3 4 3.285714
## 68 4 3 3 5 5 3 4 3.142857
## 69 4 4 3 4 4 4 3 3.000000
## 70 4 3 4 4 5 4 4 3.285714
## 71 3 3 4 5 3 3 4 2.857143
## 72 4 4 2 4 5 3 4 3.142857
## 73 3 3 4 4 4 2 2 2.571429
## 74 4 3 3 3 3 1 2 2.285714
## 75 4 2 4 3 4 3 4 3.000000
## 76 3 2 3 5 5 3 4 3.285714
## 77 3 2 4 2 4 2 4 2.714286
## 78 3 2 4 2 4 2 2 2.428571
## 79 3 2 3 2 3 2 3 2.428571
## 80 2 3 4 4 4 4 3 3.285714
## 81 3 2 3 5 4 3 3 3.142857
## 82 3 2 2 4 5 2 4 3.000000
## 83 3 4 3 5 5 3 3 3.571429
## 84 3 3 4 3 5 3 4 3.428571
## 85 3 2 4 4 5 3 3 3.428571
## 86 3 3 4 4 3 3 3 3.285714
## 87 3 2 4 4 3 1 4 3.000000
## 88 3 4 2 5 5 4 3 3.857143
## 89 4 3 2 4 5 1 4 3.428571
## 90 3 3 1 4 4 1 2 2.714286
## 91 3 2 4 2 3 3 3 3.000000
## 92 2 2 4 4 5 4 3 3.714286
## 93 3 2 3 3 5 3 2 3.428571
## 94 3 3 2 3 3 2 4 3.285714
## 95 3 2 3 2 3 2 4 3.285714
## 96 3 3 3 3 5 1 3 3.714286
## 97 4 2 2 5 3 2 2 3.714286
## 98 2 2 2 2 4 2 4 3.571429
## 99 2 3 3 5 1 3 1 3.571429
## 100 2 2 3 1 2 1 4 3.142857
## 101 2 2 4 2 3 2 3 3.571429
## 102 3 2 2 3 3 1 3 3.571429
## 103 2 2 2 4 5 2 4 4.142857
## 104 2 2 3 2 2 1 2 3.428571
## 105 2 2 2 2 2 1 3 3.571429
## 106 4 2 2 2 2 3 2 4.000000
## 107 3 3 3 3 1 2 2 4.000000
## 108 2 2 2 2 2 1 3 3.571429
## 109 3 1 1 1 1 1 1 3.000000
## 110 2 2 1 2 1 NA 2 3.428571
## 111 3 1 2 1 2 3 3 4.000000
## 112 3 2 3 1 3 2 1 4.000000
## 113 3 2 1 1 1 1 1 3.428571
## 114 3 2 1 2 2 1 2 3.857143
## 115 3 1 2 2 2 3 1 4.142857
## 116 2 3 1 4 3 1 1 4.285714
## 117 3 2 2 1 1 2 3 4.142857
## 118 2 2 2 2 2 2 2 4.142857
## 119 3 2 2 2 3 2 1 4.285714
## 120 3 2 2 2 3 1 2 4.285714
## 121 2 2 2 2 3 2 3 4.428571
## 122 3 2 2 1 1 1 2 4.000000
## 123 1 3 4 2 2 2 2 4.571429
## 124 3 2 2 1 1 2 2 4.142857
## 125 3 2 2 2 2 2 1 4.428571
## 126 2 3 2 2 1 2 2 4.428571
## 127 2 2 1 2 1 2 2 4.142857
## 128 3 3 2 1 2 1 1 4.285714
## 129 2 3 2 1 2 2 2 4.428571
## 130 2 2 2 2 2 1 1 4.285714
## 131 3 2 2 1 1 1 1 4.142857
## 132 2 2 2 2 1 1 1 4.285714
## 133 2 2 2 2 1 1 1 4.285714
## 134 3 3 1 1 1 1 1 4.285714
## 135 3 2 1 5 1 1 1 4.714286
## 136 3 2 2 2 2 1 1 4.571429
## 137 4 2 1 1 1 1 1 4.428571
## 138 2 2 2 1 2 2 1 4.571429
## 139 3 2 1 1 1 2 1 4.428571
## 140 2 2 2 1 1 2 3 4.714286
## 141 2 2 1 2 2 2 1 4.571429
## 142 4 2 2 1 1 1 1 4.571429
## 143 4 1 2 1 1 1 1 4.571429
## 144 2 2 2 1 2 1 1 4.571429
## 145 3 2 1 1 1 1 1 4.571429
## 146 2 2 1 2 1 1 1 4.714286
## 147 1 1 1 1 1 1 1 4.428571
## 148 3 1 1 1 1 1 1 4.857143
## 149 2 1 2 1 1 1 1 4.857143
## 150 2 1 1 1 1 1 2 4.857143
## 151 1 1 1 1 1 1 1 4.571429
## 152 2 1 2 1 1 1 1 4.857143
## 153 2 1 1 1 1 1 1 4.857143
## 154 1 1 1 2 1 1 1 5.000000
## 155 1 1 1 1 1 1 1 5.000000
## Avg_DisLikelihood Diff_Likelihood abs_diff
## 1 5.000000 -4.0000000 4.0000000
## 2 4.571429 -3.5714286 3.5714286
## 3 4.714286 -3.5714286 3.5714286
## 4 4.571429 -3.4285714 3.4285714
## 5 4.571429 -3.1428571 3.1428571
## 6 4.285714 -3.1428571 3.1428571
## 7 3.857143 -2.8571429 2.8571429
## 8 4.571429 -2.7142857 2.7142857
## 9 4.428571 -2.7142857 2.7142857
## 10 4.428571 -2.4285714 2.4285714
## 11 4.428571 -2.2857143 2.2857143
## 12 4.142857 -2.2857143 2.2857143
## 13 4.142857 -2.1428571 2.1428571
## 14 4.142857 -2.1428571 2.1428571
## 15 4.428571 -2.0000000 2.0000000
## 16 4.142857 -2.0000000 2.0000000
## 17 4.571429 -2.0000000 2.0000000
## 18 3.428571 -2.0000000 2.0000000
## 19 4.571429 -2.0000000 2.0000000
## 20 4.000000 -2.0000000 2.0000000
## 21 4.000000 -1.8571429 1.8571429
## 22 4.571429 -1.8571429 1.8571429
## 23 4.285714 -1.8571429 1.8571429
## 24 3.857143 -1.8571429 1.8571429
## 25 3.714286 -1.8571429 1.8571429
## 26 4.285714 -1.8571429 1.8571429
## 27 3.571429 -1.7142857 1.7142857
## 28 3.857143 -1.7142857 1.7142857
## 29 3.714286 -1.7142857 1.7142857
## 30 3.714286 -1.7142857 1.7142857
## 31 4.428571 -1.7142857 1.7142857
## 32 3.714286 -1.7142857 1.7142857
## 33 3.857143 -1.5714286 1.5714286
## 34 3.285714 -1.5714286 1.5714286
## 35 4.142857 -1.5714286 1.5714286
## 36 3.714286 -1.5714286 1.5714286
## 37 3.857143 -1.4285714 1.4285714
## 38 4.000000 -1.4285714 1.4285714
## 39 3.857143 -1.4285714 1.4285714
## 40 3.857143 -1.4285714 1.4285714
## 41 3.571429 -1.2857143 1.2857143
## 42 4.000000 -1.2857143 1.2857143
## 43 3.857143 -1.2857143 1.2857143
## 44 4.142857 -1.2857143 1.2857143
## 45 3.857143 -1.2857143 1.2857143
## 46 3.857143 -1.2857143 1.2857143
## 47 4.142857 -1.1428571 1.1428571
## 48 3.857143 -1.1428571 1.1428571
## 49 3.714286 -1.1428571 1.1428571
## 50 2.857143 -1.1428571 1.1428571
## 51 4.000000 -1.1428571 1.1428571
## 52 4.000000 -1.0000000 1.0000000
## 53 3.714286 -1.0000000 1.0000000
## 54 4.000000 -1.0000000 1.0000000
## 55 3.428571 -1.0000000 1.0000000
## 56 3.000000 -1.0000000 1.0000000
## 57 4.000000 -1.0000000 1.0000000
## 58 3.857143 -1.0000000 1.0000000
## 59 3.714286 -1.0000000 1.0000000
## 60 3.857143 -0.8571429 0.8571429
## 61 3.428571 -0.8571429 0.8571429
## 62 4.000000 -0.8571429 0.8571429
## 63 3.428571 -0.8571429 0.8571429
## 64 3.428571 -0.8571429 0.8571429
## 65 3.428571 -0.8571429 0.8571429
## 66 3.714286 -0.8571429 0.8571429
## 67 4.000000 -0.7142857 0.7142857
## 68 3.857143 -0.7142857 0.7142857
## 69 3.714286 -0.7142857 0.7142857
## 70 4.000000 -0.7142857 0.7142857
## 71 3.571429 -0.7142857 0.7142857
## 72 3.714286 -0.5714286 0.5714286
## 73 3.142857 -0.5714286 0.5714286
## 74 2.714286 -0.4285714 0.4285714
## 75 3.428571 -0.4285714 0.4285714
## 76 3.571429 -0.2857143 0.2857143
## 77 3.000000 -0.2857143 0.2857143
## 78 2.714286 -0.2857143 0.2857143
## 79 2.571429 -0.1428571 0.1428571
## 80 3.428571 -0.1428571 0.1428571
## 81 3.285714 -0.1428571 0.1428571
## 82 3.142857 -0.1428571 0.1428571
## 83 3.714286 -0.1428571 0.1428571
## 84 3.571429 -0.1428571 0.1428571
## 85 3.428571 0.0000000 0.0000000
## 86 3.285714 0.0000000 0.0000000
## 87 3.000000 0.0000000 0.0000000
## 88 3.714286 0.1428571 0.1428571
## 89 3.285714 0.1428571 0.1428571
## 90 2.571429 0.1428571 0.1428571
## 91 2.857143 0.1428571 0.1428571
## 92 3.428571 0.2857143 0.2857143
## 93 3.000000 0.4285714 0.4285714
## 94 2.857143 0.4285714 0.4285714
## 95 2.714286 0.5714286 0.5714286
## 96 3.000000 0.7142857 0.7142857
## 97 2.857143 0.8571429 0.8571429
## 98 2.571429 1.0000000 1.0000000
## 99 2.571429 1.0000000 1.0000000
## 100 2.142857 1.0000000 1.0000000
## 101 2.571429 1.0000000 1.0000000
## 102 2.428571 1.1428571 1.1428571
## 103 3.000000 1.1428571 1.1428571
## 104 2.000000 1.4285714 1.4285714
## 105 2.000000 1.5714286 1.5714286
## 106 2.428571 1.5714286 1.5714286
## 107 2.428571 1.5714286 1.5714286
## 108 2.000000 1.5714286 1.5714286
## 109 1.285714 1.7142857 1.7142857
## 110 1.666667 1.7619048 1.7619048
## 111 2.142857 1.8571429 1.8571429
## 112 2.142857 1.8571429 1.8571429
## 113 1.428571 2.0000000 2.0000000
## 114 1.857143 2.0000000 2.0000000
## 115 2.000000 2.1428571 2.1428571
## 116 2.142857 2.1428571 2.1428571
## 117 2.000000 2.1428571 2.1428571
## 118 2.000000 2.1428571 2.1428571
## 119 2.142857 2.1428571 2.1428571
## 120 2.142857 2.1428571 2.1428571
## 121 2.285714 2.1428571 2.1428571
## 122 1.714286 2.2857143 2.2857143
## 123 2.285714 2.2857143 2.2857143
## 124 1.857143 2.2857143 2.2857143
## 125 2.000000 2.4285714 2.4285714
## 126 2.000000 2.4285714 2.4285714
## 127 1.714286 2.4285714 2.4285714
## 128 1.857143 2.4285714 2.4285714
## 129 2.000000 2.4285714 2.4285714
## 130 1.714286 2.5714286 2.5714286
## 131 1.571429 2.5714286 2.5714286
## 132 1.571429 2.7142857 2.7142857
## 133 1.571429 2.7142857 2.7142857
## 134 1.571429 2.7142857 2.7142857
## 135 2.000000 2.7142857 2.7142857
## 136 1.857143 2.7142857 2.7142857
## 137 1.571429 2.8571429 2.8571429
## 138 1.714286 2.8571429 2.8571429
## 139 1.571429 2.8571429 2.8571429
## 140 1.857143 2.8571429 2.8571429
## 141 1.714286 2.8571429 2.8571429
## 142 1.714286 2.8571429 2.8571429
## 143 1.571429 3.0000000 3.0000000
## 144 1.571429 3.0000000 3.0000000
## 145 1.428571 3.1428571 3.1428571
## 146 1.428571 3.2857143 3.2857143
## 147 1.000000 3.4285714 3.4285714
## 148 1.285714 3.5714286 3.5714286
## 149 1.285714 3.5714286 3.5714286
## 150 1.285714 3.5714286 3.5714286
## 151 1.000000 3.5714286 3.5714286
## 152 1.285714 3.5714286 3.5714286
## 153 1.142857 3.7142857 3.7142857
## 154 1.142857 3.8571429 3.8571429
## 155 1.000000 4.0000000 4.0000000